Overview

Dataset statistics

Number of variables8
Number of observations703000
Missing cells2466634
Missing cells (%)43.9%
Duplicate rows55
Duplicate rows (%)< 0.1%
Total size in memory42.9 MiB
Average record size in memory64.0 B

Variable types

Numeric8

Alerts

Dataset has 55 (< 0.1%) duplicate rowsDuplicates
reflectivity is highly overall correlated with total_powerHigh correlation
total_power is highly overall correlated with reflectivityHigh correlation
reflectivity has 593838 (84.5%) missing valuesMissing
total_power has 562225 (80.0%) missing valuesMissing
velocity has 651972 (92.7%) missing valuesMissing
spectrum_width has 658599 (93.7%) missing valuesMissing

Reproduction

Analysis started2024-04-22 10:26:24.190508
Analysis finished2024-04-22 10:26:32.197596
Duration8.01 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

longitude
Real number (ℝ)

Distinct636062
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.686026
Minimum7.9688983
Maximum13.349995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 MiB
2024-04-22T17:26:32.247088image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum7.9688983
5-th percentile8.774408
Q110.00852
median10.673027
Q311.376181
95-th percentile12.586302
Maximum13.349995
Range5.3810967
Interquartile range (IQR)1.3676605

Descriptive statistics

Standard deviation1.0897991
Coefficient of variation (CV)0.10198358
Kurtosis-0.26925643
Mean10.686026
Median Absolute Deviation (MAD)0.683974
Skewness-0.014574397
Sum7512276.3
Variance1.1876622
MonotonicityNot monotonic
2024-04-22T17:26:32.319580image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.65961 1407
 
0.2%
10.65966 7
 
< 0.1%
10.659811 7
 
< 0.1%
10.659615 7
 
< 0.1%
10.659808 6
 
< 0.1%
10.659659 6
 
< 0.1%
10.659332 6
 
< 0.1%
10.659616 6
 
< 0.1%
10.708096 6
 
< 0.1%
10.659797 6
 
< 0.1%
Other values (636052) 701536
99.8%
ValueCountFrequency (%)
7.9688983 1
< 0.1%
7.969086 1
< 0.1%
7.9692225 1
< 0.1%
7.9704094 1
< 0.1%
7.9705014 1
< 0.1%
7.9718328 1
< 0.1%
7.97201 1
< 0.1%
7.972188 1
< 0.1%
7.9725595 1
< 0.1%
7.9731936 1
< 0.1%
ValueCountFrequency (%)
13.349995 1
< 0.1%
13.349702 1
< 0.1%
13.349603 1
< 0.1%
13.348747 1
< 0.1%
13.348638 1
< 0.1%
13.347436 1
< 0.1%
13.347107 1
< 0.1%
13.346885 1
< 0.1%
13.346762 1
< 0.1%
13.346106 1
< 0.1%

latitude
Real number (ℝ)

Distinct390890
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.74303
Minimum103.99098
Maximum109.46626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 MiB
2024-04-22T17:26:32.387769image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum103.99098
5-th percentile104.76653
Q1106.03384
median106.74245
Q3107.45951
95-th percentile108.69125
Maximum109.46626
Range5.475275
Interquartile range (IQR)1.4256725

Descriptive statistics

Standard deviation1.1243545
Coefficient of variation (CV)0.010533283
Kurtosis-0.31753025
Mean106.74303
Median Absolute Deviation (MAD)0.71285
Skewness-0.028459393
Sum75040350
Variance1.2641731
MonotonicityNot monotonic
2024-04-22T17:26:32.456556image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106.728325 1410
 
0.2%
106.728035 25
 
< 0.1%
106.72947 24
 
< 0.1%
106.72823 23
 
< 0.1%
106.7326 23
 
< 0.1%
106.72993 22
 
< 0.1%
106.72797 20
 
< 0.1%
106.73175 19
 
< 0.1%
106.73312 18
 
< 0.1%
106.728165 18
 
< 0.1%
Other values (390880) 701398
99.8%
ValueCountFrequency (%)
103.99098 1
< 0.1%
103.991005 1
< 0.1%
103.991875 1
< 0.1%
103.99193 1
< 0.1%
103.99335 1
< 0.1%
103.99346 1
< 0.1%
103.99348 1
< 0.1%
103.993614 1
< 0.1%
103.99411 1
< 0.1%
103.99427 1
< 0.1%
ValueCountFrequency (%)
109.466255 1
< 0.1%
109.46624 1
< 0.1%
109.46547 1
< 0.1%
109.465324 1
< 0.1%
109.46379 1
< 0.1%
109.46374 1
< 0.1%
109.463356 1
< 0.1%
109.463326 1
< 0.1%
109.4626 1
< 0.1%
109.46243 1
< 0.1%

altitude
Real number (ℝ)

Distinct23421
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7129.0934
Minimum10
Maximum25398
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 MiB
2024-04-22T17:26:32.523912image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile365.95
Q12389
median5770
Q310784
95-th percentile18470
Maximum25398
Range25388
Interquartile range (IQR)8395

Descriptive statistics

Standard deviation5742.2345
Coefficient of variation (CV)0.80546491
Kurtosis-0.0088721892
Mean7129.0934
Median Absolute Deviation (MAD)3892
Skewness0.86464998
Sum5.0117526 × 109
Variance32973257
MonotonicityNot monotonic
2024-04-22T17:26:32.596398image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 1406
 
0.2%
26 382
 
0.1%
59 306
 
< 0.1%
35 289
 
< 0.1%
85 272
 
< 0.1%
92 250
 
< 0.1%
43 240
 
< 0.1%
60 230
 
< 0.1%
86 225
 
< 0.1%
48 211
 
< 0.1%
Other values (23411) 699189
99.5%
ValueCountFrequency (%)
10 1406
0.2%
13 54
 
< 0.1%
14 129
 
< 0.1%
15 103
 
< 0.1%
16 19
 
< 0.1%
17 37
 
< 0.1%
18 78
 
< 0.1%
19 64
 
< 0.1%
20 62
 
< 0.1%
21 81
 
< 0.1%
ValueCountFrequency (%)
25398 1
< 0.1%
25336 1
< 0.1%
25326 1
< 0.1%
25298 2
< 0.1%
25275 1
< 0.1%
25265 1
< 0.1%
25241 1
< 0.1%
25237 2
< 0.1%
25214 1
< 0.1%
25204 1
< 0.1%

reflectivity
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct5532
Distinct (%)5.1%
Missing593838
Missing (%)84.5%
Infinite0
Infinite (%)0.0%
Mean4.2562447
Minimum-23.93
Maximum59.27
Zeros47
Zeros (%)< 0.1%
Negative38566
Negative (%)5.5%
Memory size5.4 MiB
2024-04-22T17:26:32.672107image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-23.93
5-th percentile-13.99
Q1-4.16
median4.58
Q311.82
95-th percentile23.2295
Maximum59.27
Range83.2
Interquartile range (IQR)15.98

Descriptive statistics

Standard deviation11.177856
Coefficient of variation (CV)2.6262251
Kurtosis-0.51854467
Mean4.2562447
Median Absolute Deviation (MAD)7.92
Skewness0.096668684
Sum464620.18
Variance124.94447
MonotonicityNot monotonic
2024-04-22T17:26:32.745240image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.46 60
 
< 0.1%
7.41 57
 
< 0.1%
6.71 57
 
< 0.1%
8.05 56
 
< 0.1%
7.01 56
 
< 0.1%
3.98 56
 
< 0.1%
8.61 56
 
< 0.1%
8.74 55
 
< 0.1%
5.19 54
 
< 0.1%
6.44 54
 
< 0.1%
Other values (5522) 108601
 
15.4%
(Missing) 593838
84.5%
ValueCountFrequency (%)
-23.93 1
< 0.1%
-23.63 1
< 0.1%
-23.18 1
< 0.1%
-22.84 1
< 0.1%
-22.56 1
< 0.1%
-22.45 1
< 0.1%
-22.41 1
< 0.1%
-22.3 1
< 0.1%
-22.26 1
< 0.1%
-22.17 1
< 0.1%
ValueCountFrequency (%)
59.27 1
< 0.1%
56.65 1
< 0.1%
51.95 1
< 0.1%
49.37 1
< 0.1%
49.09 1
< 0.1%
48.92 1
< 0.1%
47.84 1
< 0.1%
47.8 1
< 0.1%
47.68 1
< 0.1%
47.42 1
< 0.1%

total_power
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7201
Distinct (%)5.1%
Missing562225
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean8.8439624
Minimum-19.03
Maximum75.66
Zeros53
Zeros (%)< 0.1%
Negative36050
Negative (%)5.1%
Memory size5.4 MiB
2024-04-22T17:26:32.822504image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-19.03
5-th percentile-9.233
Q1-0.23
median7.53
Q316.56
95-th percentile30.74
Maximum75.66
Range94.69
Interquartile range (IQR)16.79

Descriptive statistics

Standard deviation12.6009
Coefficient of variation (CV)1.4248025
Kurtosis0.76134825
Mean8.8439624
Median Absolute Deviation (MAD)8.32
Skewness0.68897027
Sum1245008.8
Variance158.78268
MonotonicityNot monotonic
2024-04-22T17:26:32.904433image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.33 72
 
< 0.1%
4.63 70
 
< 0.1%
23.35 69
 
< 0.1%
7.66 68
 
< 0.1%
6.2 68
 
< 0.1%
6.53 67
 
< 0.1%
7.26 67
 
< 0.1%
5.95 66
 
< 0.1%
4.59 66
 
< 0.1%
5.37 66
 
< 0.1%
Other values (7191) 140096
 
19.9%
(Missing) 562225
80.0%
ValueCountFrequency (%)
-19.03 1
< 0.1%
-19.02 1
< 0.1%
-18.97 1
< 0.1%
-18.76 1
< 0.1%
-18.66 1
< 0.1%
-18.57 1
< 0.1%
-18.53 1
< 0.1%
-18.49 1
< 0.1%
-18.39 1
< 0.1%
-18.38 1
< 0.1%
ValueCountFrequency (%)
75.66 1
< 0.1%
74.28 1
< 0.1%
70.81 1
< 0.1%
70.67 1
< 0.1%
70.22 1
< 0.1%
69.81 1
< 0.1%
69.42 1
< 0.1%
69.13 1
< 0.1%
68.7 1
< 0.1%
68.59 1
< 0.1%

velocity
Real number (ℝ)

MISSING 

Distinct805
Distinct (%)1.6%
Missing651972
Missing (%)92.7%
Infinite0
Infinite (%)0.0%
Mean-0.13457514
Minimum-4.02
Maximum4.02
Zeros42
Zeros (%)< 0.1%
Negative26646
Negative (%)3.8%
Memory size5.4 MiB
2024-04-22T17:26:32.977678image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-4.02
5-th percentile-3.69
Q1-2.39
median-0.26
Q32.04
95-th percentile3.68
Maximum4.02
Range8.04
Interquartile range (IQR)4.43

Descriptive statistics

Standard deviation2.439908
Coefficient of variation (CV)-18.130452
Kurtosis-1.3011469
Mean-0.13457514
Median Absolute Deviation (MAD)2.21
Skewness0.074616526
Sum-6867.1
Variance5.953151
MonotonicityNot monotonic
2024-04-22T17:26:33.056604image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.88 115
 
< 0.1%
-3.6 102
 
< 0.1%
-3.67 98
 
< 0.1%
-3.39 97
 
< 0.1%
-3.51 96
 
< 0.1%
-3.28 96
 
< 0.1%
-3.87 95
 
< 0.1%
3.72 95
 
< 0.1%
-3.61 95
 
< 0.1%
-3.47 95
 
< 0.1%
Other values (795) 50044
 
7.1%
(Missing) 651972
92.7%
ValueCountFrequency (%)
-4.02 33
 
< 0.1%
-4.01 93
< 0.1%
-4 75
< 0.1%
-3.99 68
< 0.1%
-3.98 72
< 0.1%
-3.97 78
< 0.1%
-3.96 60
< 0.1%
-3.95 73
< 0.1%
-3.94 72
< 0.1%
-3.93 70
< 0.1%
ValueCountFrequency (%)
4.02 34
 
< 0.1%
4.01 77
< 0.1%
4 80
< 0.1%
3.99 64
< 0.1%
3.98 82
< 0.1%
3.97 80
< 0.1%
3.96 82
< 0.1%
3.95 89
< 0.1%
3.94 85
< 0.1%
3.93 71
< 0.1%

spectrum_width
Real number (ℝ)

MISSING 

Distinct219
Distinct (%)0.5%
Missing658599
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean0.73154997
Minimum0.01
Maximum2.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 MiB
2024-04-22T17:26:33.133578image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.28
Q10.53
median0.71
Q30.91
95-th percentile1.27
Maximum2.35
Range2.34
Interquartile range (IQR)0.38

Descriptive statistics

Standard deviation0.30548474
Coefficient of variation (CV)0.41758561
Kurtosis0.7527892
Mean0.73154997
Median Absolute Deviation (MAD)0.19
Skewness0.47709307
Sum32481.55
Variance0.093320926
MonotonicityNot monotonic
2024-04-22T17:26:33.205379image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.65 678
 
0.1%
0.61 676
 
0.1%
0.62 675
 
0.1%
0.6 649
 
0.1%
0.69 649
 
0.1%
0.68 646
 
0.1%
0.64 635
 
0.1%
0.71 634
 
0.1%
0.58 631
 
0.1%
0.72 626
 
0.1%
Other values (209) 37902
 
5.4%
(Missing) 658599
93.7%
ValueCountFrequency (%)
0.01 611
0.1%
0.02 5
 
< 0.1%
0.03 6
 
< 0.1%
0.04 6
 
< 0.1%
0.05 17
 
< 0.1%
0.06 16
 
< 0.1%
0.07 22
 
< 0.1%
0.08 20
 
< 0.1%
0.09 28
 
< 0.1%
0.1 30
 
< 0.1%
ValueCountFrequency (%)
2.35 1
< 0.1%
2.33 1
< 0.1%
2.31 1
< 0.1%
2.26 1
< 0.1%
2.23 1
< 0.1%
2.22 2
< 0.1%
2.21 1
< 0.1%
2.2 1
< 0.1%
2.16 1
< 0.1%
2.14 1
< 0.1%

time
Real number (ℝ)

Distinct160
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.385491
Minimum0
Maximum172
Zeros4000
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size5.4 MiB
2024-04-22T17:26:33.349693image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q148
median90
Q3133
95-th percentile164
Maximum172
Range172
Interquartile range (IQR)85

Descriptive statistics

Standard deviation50.443468
Coefficient of variation (CV)0.57725222
Kurtosis-1.1899074
Mean87.385491
Median Absolute Deviation (MAD)42
Skewness-0.079872632
Sum61432000
Variance2544.5435
MonotonicityNot monotonic
2024-04-22T17:26:33.420759image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83 5500
 
0.8%
96 5500
 
0.8%
116 5500
 
0.8%
147 5500
 
0.8%
135 5500
 
0.8%
167 5500
 
0.8%
71 5500
 
0.8%
54 5500
 
0.8%
155 5500
 
0.8%
59 5000
 
0.7%
Other values (150) 648500
92.2%
ValueCountFrequency (%)
0 4000
0.6%
1 4500
0.6%
2 5000
0.7%
3 4000
0.6%
4 4500
0.6%
5 4500
0.6%
6 5000
0.7%
7 3500
0.5%
8 5000
0.7%
9 4500
0.6%
ValueCountFrequency (%)
172 500
 
0.1%
171 4000
0.6%
170 4000
0.6%
169 4500
0.6%
168 4000
0.6%
167 5500
0.8%
166 4500
0.6%
165 4000
0.6%
164 5000
0.7%
163 4500
0.6%

Interactions

2024-04-22T17:26:30.701757image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.525605image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.105199image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.646040image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.165210image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.039316image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.681318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.175330image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.798014image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.608153image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.180513image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.724318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.223487image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.116794image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.749258image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.234677image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.875145image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.696211image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.262329image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.803435image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.279900image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.209435image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.807827image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.289830image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.935318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.758949image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.322500image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.858103image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.337696image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.395165image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.865975image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.350772image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.993821image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.821510image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.376609image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.916901image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.390062image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.454323image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.922819image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.420477image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:31.049507image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.876040image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.430949image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.970595image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.578501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.508435image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.977779image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.485834image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:31.116327image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:26.940298image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.491306image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.028650image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.783318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.566116image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.039074image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.543677image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:31.209166image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.023145image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:27.563405image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.103542image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:28.841112image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:29.624820image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.113776image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-22T17:26:30.595418image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2024-04-22T17:26:33.472744image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
altitudelatitudelongitudereflectivityspectrum_widthtimetotal_powervelocity
altitude1.000-0.008-0.0050.3630.0480.456-0.160-0.041
latitude-0.0081.000-0.022-0.1350.016-0.060-0.0360.055
longitude-0.005-0.0221.0000.1790.043-0.1520.039-0.175
reflectivity0.363-0.1350.1791.0000.134-0.2070.7750.013
spectrum_width0.0480.0160.0430.1341.000-0.0980.1370.027
time0.456-0.060-0.152-0.207-0.0981.000-0.1660.015
total_power-0.160-0.0360.0390.7750.137-0.1661.0000.027
velocity-0.0410.055-0.1750.0130.0270.0150.0271.000

Missing values

2024-04-22T17:26:31.297646image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T17:26:31.530298image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
010.659610106.72832510.03.7523.07NaNNaN15.0
110.665006106.72835015.017.9739.31NaNNaN15.0
210.670401106.72836021.011.7931.69NaNNaN15.0
310.675796106.72838027.011.7523.95NaNNaN15.0
410.681192106.72839034.08.2930.16NaNNaN15.0
510.686587106.72842039.00.9825.60NaNNaN15.0
610.691983106.72843046.0NaN34.03NaN1.4815.0
710.697379106.72845052.0NaN44.41NaN0.9415.0
810.702774106.72847058.0NaN56.36NaNNaN15.0
910.708171106.72849064.0NaN52.54NaNNaN15.0
longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
70299013.290660106.6851824244.0NaNNaNNaNNaN133.0
70299113.296014106.6850924304.0NaNNaNNaNNaN133.0
70299213.301366106.6850024364.0NaNNaNNaNNaN133.0
70299313.306719106.6849124424.0NaNNaNNaNNaN133.0
70299413.312071106.6848224483.0NaNNaNNaNNaN133.0
70299513.317425106.6847424543.0NaNNaNNaNNaN133.0
70299613.322777106.6846524604.0NaNNaNNaNNaN133.0
70299713.328129106.6845624663.0NaNNaNNaNNaN133.0
70299813.333482106.6844824724.0NaNNaNNaNNaN133.0
70299913.338835106.6843924784.0NaNNaNNaNNaN133.0

Duplicate rows

Most frequently occurring

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime# duplicates
1410.65961106.72832510.0NaN23.13NaNNaN160.04
410.65961106.72832510.0NaN22.96NaNNaN49.03
810.65961106.72832510.0NaN23.02NaNNaN8.03
1610.65961106.72832510.0NaN23.14NaNNaN167.03
2510.65961106.72832510.0NaN23.18NaNNaN163.03
2710.65961106.72832510.0NaN23.19NaNNaN157.03
2810.65961106.72832510.0NaN23.19NaNNaN164.03
3110.65961106.72832510.0NaN23.24NaNNaN66.03
3910.65961106.72832510.0NaN23.32NaNNaN116.03
4410.65961106.72832510.0NaN23.33NaNNaN125.03